Experience - 5-9 Years Responsibilities Design and develop contemporary front-end interfaces (React, Angular, Streamlit) tailored for AI-driven workflows, chat interfaces, dashboards, and model output visualization. Build backend APIs and microservices (Node.js, Python Flask/FastAPI) to serve LLMs, RAG pipelines, vector DBs, and user facing applications securely and efficiently. Integrate AI/ML models through REST, WebSockets, or gRPC, ensuring low latency, scalability, and reliable inference pipelines. Implement real-time AI features such as chatbots, conversational UI, document processing apps, recommendation engines, and intelligent agents. Automate workflows using UiPath or similar orchestration tools when AI-driven tasks require robotic or enterprise automation. Develop and maintain reusable UI components for prompt interfaces,



model monitoring, and human-in-the-loop review flows. Write unit, integration, and end-to-end tests to ensure stability, correctness, and reliability across AI application layers. Optimize performance, manage deployments, and scale applications using CI/CD pipelines, Docker, Kubernetes, and cloud native infrastructure. Collaborate with AI/ML engineers to connect UI/UX requirements with underlying model behavior, context pipelines, and evaluation workflows. Technology Stack Blackened- Python Front-end- React.js/Javascript Cloud- GCP AI tech- Agentic AI,Langraph,LLM, RAG, AI/ML, chatbot agent

📌 Fullstack AI Engineer (React "agentic AI" GCP CLoud) (Uttar Pradesh)
🏢 Innodata
📍 Uttar Pradesh